{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Using Variational Autoencoder and Deep Feature Loss to Generate Faces"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "From the \"Using Variational Autoencoder to Generate Faces\" example, we see that using VAE, we can generate realistic human faces, but the generated image is a little blury. Though, you can continue to tuning the hyper paramters or using more data to get a better result, in this example, we adopted the approach in [this paper](https://arxiv.org/abs/1610.00291). That is, instead of using pixel-by-pixel loss of between the original images and the generated images, we use the feature map generated by a pre-trained CNN network to define a feature perceptual loss. As you will see, the generated images will become more vivid."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from bigdl.nn.layer import *\n",
    "from bigdl.nn.criterion import *\n",
    "from bigdl.optim.optimizer import *\n",
    "from bigdl.dataset import mnist\n",
    "import datetime as dt\n",
    "from glob import glob\n",
    "import os\n",
    "import numpy as np\n",
    "from utils import *\n",
    "import imageio\n",
    "\n",
    "image_size = 148\n",
    "Z_DIM = 100\n",
    "ENCODER_FILTER_NUM = 32\n",
    "\n",
    "# we use the vgg16 model, it should work on other popular CNN models\n",
    "# You can download them here (https://github.com/intel-analytics/analytics-zoo/tree/master/models\n",
    "# download the data CelebA, and may repalce with your own data path\n",
    "DATA_PATH = os.getenv(\"ANALYTICS_ZOO_HOME\") + \"/apps/variational-autoencoder/img_align_celeba\"\n",
    "VGG_PATH = os.getenv(\"ANALYTICS_ZOO_HOME\")+\"/apps/variational-autoencoder/analytics-zoo_vgg-16_imagenet_0.1.0.model\"\n",
    "\n",
    "from zoo.common.nncontext import *\n",
    "sc = init_nncontext(\"Variational Autoencoder Example\")\n",
    "sc.addFile(os.getenv(\"ANALYTICS_ZOO_HOME\")+\"/apps/variational-autoencoder/utils.py\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Define the Model"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We are uing the same model as \"Using Variational Autoencoder to Generate Faces\" example."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "def conv_bn_lrelu(in_channels, out_channles, kw=4, kh=4, sw=2, sh=2, pw=-1, ph=-1):\n",
    "    model = Sequential()\n",
    "    model.add(SpatialConvolution(in_channels, out_channles, kw, kh, sw, sh, pw, ph))\n",
    "    model.add(SpatialBatchNormalization(out_channles))\n",
    "    model.add(LeakyReLU(0.2))\n",
    "    return model\n",
    "\n",
    "def upsample_conv_bn_lrelu(in_channels, out_channles, out_width, out_height, kw=3, kh=3, sw=1, sh=1, pw=-1, ph=-1):\n",
    "    model = Sequential()\n",
    "    model.add(ResizeBilinear(out_width, out_height))\n",
    "    model.add(SpatialConvolution(in_channels, out_channles, kw, kh, sw, sh, pw, ph))\n",
    "    model.add(SpatialBatchNormalization(out_channles))\n",
    "    model.add(LeakyReLU(0.2))\n",
    "    return model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_encoder_cnn():\n",
    "    input0 = Input()\n",
    "    \n",
    "    #CONV\n",
    "    conv1 = conv_bn_lrelu(3, ENCODER_FILTER_NUM)(input0) # 32 * 32 * 32\n",
    "    conv2 = conv_bn_lrelu(ENCODER_FILTER_NUM, ENCODER_FILTER_NUM*2)(conv1) # 16 * 16 * 64\n",
    "    conv3 = conv_bn_lrelu(ENCODER_FILTER_NUM*2, ENCODER_FILTER_NUM*4)(conv2) # 8 * 8 * 128\n",
    "    conv4 = conv_bn_lrelu(ENCODER_FILTER_NUM*4, ENCODER_FILTER_NUM*8)(conv3) # 4 * 4 * 256\n",
    "    view = View([4*4*ENCODER_FILTER_NUM*8])(conv4)\n",
    "    \n",
    "    # fully connected to generate mean and log-variance\n",
    "    mean = Linear(4*4*ENCODER_FILTER_NUM*8, Z_DIM)(view)\n",
    "    log_variance = Linear(4*4*ENCODER_FILTER_NUM*8, Z_DIM)(view)\n",
    "    \n",
    "    model = Model([input0], [mean, log_variance])\n",
    "    return model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_decoder_cnn():\n",
    "    input0 = Input()\n",
    "    \n",
    "    linear = Linear(Z_DIM, 4*4*ENCODER_FILTER_NUM*8)(input0)\n",
    "    reshape = Reshape([ENCODER_FILTER_NUM*8, 4, 4])(linear)\n",
    "    bn = SpatialBatchNormalization(ENCODER_FILTER_NUM*8)(reshape)\n",
    "    \n",
    "    # upsampling\n",
    "    up1 = upsample_conv_bn_lrelu(ENCODER_FILTER_NUM*8, ENCODER_FILTER_NUM*4, 8, 8)(bn) # 8 * 8 * 128\n",
    "    up2 = upsample_conv_bn_lrelu(ENCODER_FILTER_NUM*4, ENCODER_FILTER_NUM*2, 16, 16)(up1) # 16 * 16 * 64\n",
    "    up3 = upsample_conv_bn_lrelu(ENCODER_FILTER_NUM*2, ENCODER_FILTER_NUM, 32, 32)(up2) # 32 * 32 * 32\n",
    "    up4 = upsample_conv_bn_lrelu(ENCODER_FILTER_NUM, 3, 64, 64)(up3) # 64 * 64 * 3\n",
    "    output = Tanh()(up4)\n",
    "    \n",
    "    model = Model([input0], [output])\n",
    "    return model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_autoencoder_cnn():\n",
    "    input0 = Input()\n",
    "    encoder = get_encoder_cnn()(input0)\n",
    "    sampler = GaussianSampler()(encoder)\n",
    "    \n",
    "    decoder_model = get_decoder_cnn()\n",
    "    decoder = decoder_model(sampler)\n",
    "    \n",
    "    model = Model([input0], [encoder, decoder])\n",
    "    return model, decoder_model"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load the pre-trained CNN model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_vgg():\n",
    "    # we use the vgg16 model, it should work on other popular CNN models\n",
    "    # You can download them here (https://github.com/intel-analytics/analytics-zoo/tree/master/models)\n",
    "    vgg_whole = Model.from_jvalue(Model.loadModel(VGG_PATH).value)\n",
    "\n",
    "    # we only use one feature map here for the sake of simlicity and efficiency\n",
    "    # You can and other feature to the outputs to mix high-level and low-level\n",
    "    # feature to get higher quality images\n",
    "    outputs = [vgg_whole.node(name) for name in [\"relu1_2\"]]\n",
    "    inputs = [vgg_whole.node(name) for name in [\"data\"]]\n",
    "    \n",
    "    outputs[0].remove_next_edges()\n",
    "\n",
    "    vgg_light = Model(inputs, outputs).freeze()\n",
    "    \n",
    "    return vgg_light\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "creating: createModel\n"
     ]
    }
   ],
   "source": [
    "vgg = get_vgg()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "creating: createInput\n",
      "creating: createInput\n",
      "creating: createSequential\n",
      "creating: createSpatialConvolution\n",
      "creating: createSpatialBatchNormalization\n",
      "creating: createLeakyReLU\n",
      "creating: createSequential\n",
      "creating: createSpatialConvolution\n",
      "creating: createSpatialBatchNormalization\n",
      "creating: createLeakyReLU\n",
      "creating: createSequential\n",
      "creating: createSpatialConvolution\n",
      "creating: createSpatialBatchNormalization\n",
      "creating: createLeakyReLU\n",
      "creating: createSequential\n",
      "creating: createSpatialConvolution\n",
      "creating: createSpatialBatchNormalization\n",
      "creating: createLeakyReLU\n",
      "creating: createView\n",
      "creating: createLinear\n",
      "creating: createLinear\n",
      "creating: createModel\n",
      "creating: createGaussianSampler\n",
      "creating: createInput\n",
      "creating: createLinear\n",
      "creating: createReshape\n",
      "creating: createSpatialBatchNormalization\n",
      "creating: createSequential\n",
      "creating: createResizeBilinear\n",
      "creating: createSpatialConvolution\n",
      "creating: createSpatialBatchNormalization\n",
      "creating: createLeakyReLU\n",
      "creating: createSequential\n",
      "creating: createResizeBilinear\n",
      "creating: createSpatialConvolution\n",
      "creating: createSpatialBatchNormalization\n",
      "creating: createLeakyReLU\n",
      "creating: createSequential\n",
      "creating: createResizeBilinear\n",
      "creating: createSpatialConvolution\n",
      "creating: createSpatialBatchNormalization\n",
      "creating: createLeakyReLU\n",
      "creating: createSequential\n",
      "creating: createResizeBilinear\n",
      "creating: createSpatialConvolution\n",
      "creating: createSpatialBatchNormalization\n",
      "creating: createLeakyReLU\n",
      "creating: createTanh\n",
      "creating: createModel\n",
      "creating: createModel\n"
     ]
    }
   ],
   "source": [
    "model, decoder = get_autoencoder_cnn()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load the Datasets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_data():\n",
    "    data_files = glob(os.path.join(DATA_PATH, \"*.jpg\"))\n",
    "    \n",
    "    rdd_train_images = sc.parallelize(data_files[:100000]) \\\n",
    "                              .map(lambda path: get_image(path, image_size).transpose(2, 0, 1))\n",
    "\n",
    "    rdd_train_sample = rdd_train_images.map(lambda img: Sample.from_ndarray(img, [np.array(0.0), img]))\n",
    "    return rdd_train_sample"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_data = get_data()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Define the Training Objective"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "creating: createParallelCriterion\n",
      "creating: createKLDCriterion\n",
      "creating: createMSECriterion\n",
      "creating: createTransformerCriterion\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<bigdl.nn.criterion.ParallelCriterion at 0x7fcd11c88490>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "criterion = ParallelCriterion()\n",
    "criterion.add(KLDCriterion(), 0.005) # You may want to twick this parameter\n",
    "criterion.add(TransformerCriterion(MSECriterion(), vgg, vgg), 1.0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Define the Optimizer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "creating: createAdam\n",
      "creating: createMaxEpoch\n",
      "creating: createDistriOptimizer\n",
      "creating: createTrainSummary\n",
      "saving logs to  vae-20180509-105540\n"
     ]
    }
   ],
   "source": [
    "batch_size = 64\n",
    "\n",
    "\n",
    "# Create an Optimizer\n",
    "optimizer = Optimizer(\n",
    "    model=model,\n",
    "    training_rdd=train_data,\n",
    "    criterion=criterion,\n",
    "    optim_method=Adam(0.0005),\n",
    "    end_trigger=MaxEpoch(1),\n",
    "    batch_size=batch_size)\n",
    "\n",
    "\n",
    "app_name='vae-'+dt.datetime.now().strftime(\"%Y%m%d-%H%M%S\")\n",
    "train_summary = TrainSummary(log_dir='/tmp/vae',\n",
    "                                     app_name=app_name)\n",
    "\n",
    "\n",
    "optimizer.set_train_summary(train_summary)\n",
    "\n",
    "print (\"saving logs to \",app_name)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Spin Up the Training"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This could take a while. It took about 6 hours on a desktop with a intel i7-6700 cpu and 40GB java heap memory. You can reduce the training time by using less data (some changes in the \"Load the Dataset\" section), but the performce may not as good."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "redire_spark_logs()\n",
    "show_bigdl_info_logs()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "def gen_image_row():\n",
    "    decoder.evaluate()\n",
    "    return np.column_stack([decoder.forward(np.random.randn(1, Z_DIM)).reshape(3, 64,64).transpose(1, 2, 0) for s in range(8)])\n",
    "\n",
    "def gen_image():\n",
    "    return inverse_transform(np.row_stack([gen_image_row() for i in range(8)]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "creating: createMaxEpoch\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python2.7/dist-packages/ipykernel_launcher.py:7: DeprecationWarning: `imsave` is deprecated!\n",
      "`imsave` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\n",
      "Use ``imageio.imwrite`` instead.\n",
      "  import sys\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "creating: createMaxEpoch\n",
      "creating: createMaxEpoch\n",
      "creating: createMaxEpoch\n",
      "creating: createMaxEpoch\n"
     ]
    }
   ],
   "source": [
    "for i in range(1, 6):\n",
    "    optimizer.set_end_when(MaxEpoch(i))\n",
    "    trained_model = optimizer.optimize()\n",
    "    image = gen_image()\n",
    "    if not os.path.exists(\"./images\"):\n",
    "        os.makedirs(\"./images\")\n",
    "    if not os.path.exists(\"./models\"):\n",
    "        os.makedirs(\"./models\")\n",
    "    # you may change the following directory accordingly and make sure the directory\n",
    "    # you are writing to exists\n",
    "    imageio.imwrite(\"./images/image_vgg_%s.png\" % i, image)\n",
    "    decoder.saveModel(\"./models/decoder_vgg_%s.model\" % i, over_write = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Populating the interactive namespace from numpy and matplotlib\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python2.7/dist-packages/IPython/core/magics/pylab.py:161: UserWarning: pylab import has clobbered these variables: ['Normalize', 'imread']\n",
      "`%matplotlib` prevents importing * from pylab and numpy\n",
      "  \"\\n`%matplotlib` prevents importing * from pylab and numpy\"\n"
     ]
    }
   ],
   "source": [
    "import matplotlib\n",
    "matplotlib.use('Agg')\n",
    "%pylab inline\n",
    "\n",
    "import numpy as np\n",
    "import datetime as dt\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x7fcd102feb50>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fcd11c88310>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "loss = np.array(train_summary.read_scalar(\"Loss\"))\n",
    "\n",
    "plt.figure(figsize = (12,12))\n",
    "plt.plot(loss[:,0],loss[:,1],label='loss')\n",
    "plt.xlim(0,loss.shape[0]+10)\n",
    "plt.grid(True)\n",
    "plt.title(\"loss\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Random Sample Some Images"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7fcd0a938e90>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fcd10284d10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from matplotlib.pyplot import imshow\n",
    "img = gen_image()\n",
    "imshow(img)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.15"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
